Both Soft computing based controllers and sliding mode controllers have been utilized to regulate the output voltage of dc-dc converters in response to changes in the load and the input voltage. Although both control techniques possess desirable characteristics, they have disadvantages which prevent them from being applied extensively. Many researchers have proposed the combination of sliding m...

Soft computing is a partnership between A.I. techniques that are tolerant of imprecision, uncertainty and partial truth, with the aim of obtaining a robust solution for complex systems. Telecommunication systems are built with extensive redundancy and complexity to ensure robustness and quality of service. To facilitate this requires complex fault identification and management systems. Fault id...

This paper is directed to the question of how to model and design an efficient tool for the intelligent mapping which is based on both dynamic and efficient storage of data and soft computing. The former is performed by our method that learns how to store, search and delete the data. After pointing out the limitation of the crisp evaluation of the distance between two points, we argue in favor ...

A program to automate the finite element method (FEM) using various soft-computing techniques is presented. The overall program is discussed, and the implementations of three specific sub-problems (mesh placement, node numbering, and adaptive meshing) are described. It is also argued that the overall architecture of an “intelligent finite element package” can serve as a “test-bed” for many soft...

Managing organizational resources is a complex and difficult task at the hands of the managers. Finance, being one of those many resources, is the ‘lifeblood’ of any organization; hence its efficient and effective management is even more important. Decisions related to financial matters conventionally involve quantitative analysis and interpretation of facts and figures. These analyses are cris...

Many real-world manufacturing problems are too complex to be modelled analytically. In these scenarios simulation-based optimisation is a powerful tool to determine optimal system settings. While traditional optimisation methods have been unable to cope with the complexities of many real-world problems approached by simulation, soft computing techniques have proven to be highly useful. This pap...

Soft Computing is an emerging field that consists of complementary elements of fuzzy logic, neural computing and evolutionary computation. Soft computing techniques have found wide applications. One of the most important applications is edge detection for image segmentation. The process of partitioning a digital image into multiple regions or sets of pixels is called image segmentation. Edge is...

Most of the process systems exhibits non-linear behaviour, so conventional controllers are not able to provide accurate data. At present, various soft computing techniques are used to overcome imprecision and uncertainty effects of conventional controllers. Various soft computing techniques like fuzzy logic, genetic algorithm and particle swarm optimization have been suggested for optimum setti...

The main aim of this paper is to overcome the drawbacks of LIDAR which are non-linearity in climatic physics based on statistical modeling and evaluation. However, modeling is shown to be a successful method to forecast weather parameters by using different types of Soft Computing Techniques such as Neural Networks, Fuzzy Logic and Probability Theory which are suitable to these meteorological p...